In Figure REF , we see that HaloNet-50 with \(b=8\) , and \(h=3\)  achieves better accuracies using the same block and halo to achieve \(7\times 7\)  neighborhoods with attention masks  [1]} and the gap widens with more regularizations. This suggests that larger receptive fields are more important than inductive biases such as translational equivariance.
